WO2018075249A1 - Générateur de filtre intelligent - Google Patents

Générateur de filtre intelligent Download PDF

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Publication number
WO2018075249A1
WO2018075249A1 PCT/US2017/055191 US2017055191W WO2018075249A1 WO 2018075249 A1 WO2018075249 A1 WO 2018075249A1 US 2017055191 W US2017055191 W US 2017055191W WO 2018075249 A1 WO2018075249 A1 WO 2018075249A1
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WO
WIPO (PCT)
Prior art keywords
network
sfg
order parameter
filter
user
Prior art date
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PCT/US2017/055191
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English (en)
Inventor
Manjunath Meda Nagaraj
Imran Ahmed Ishtiaq
Jude Pragash Vedam
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Extreme Networks, Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Application filed by Extreme Networks, Inc. filed Critical Extreme Networks, Inc.
Priority to EP17862174.4A priority Critical patent/EP3529988A4/fr
Publication of WO2018075249A1 publication Critical patent/WO2018075249A1/fr

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/12—Network monitoring probes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/08—Configuration management of networks or network elements
    • H04L41/0876—Aspects of the degree of configuration automation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/22—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks comprising specially adapted graphical user interfaces [GUI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/02—Capturing of monitoring data
    • H04L43/028—Capturing of monitoring data by filtering
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition

Definitions

  • a visibility network (also known as a “visibility fabric”) is a type of network that facilitates the monitoring and analysis of traffic flowing through another, "core” network (e.g., a production network).
  • core e.g., a production network.
  • the reasons for deploying a visibility network are varied and can include network management and optimization, business intelligence/reporting, compliance validation, service assurance, security monitoring, and so on.
  • FIG. 1 depicts an example visibility network 100 according to an embodiment.
  • visibility network 100 includes a number of taps 102 that are deployed within a core network 104.
  • Taps 102 are configured to replicate data and control traffic that is exchanged between network elements in core network 104 and forward the replicated traffic to a packet broker 106 (note that, in addition to or in lieu of taps 102, one or more routers or switches in core network 104 can be tasked to replicate and forward data/control traffic to packet broker 106 using their respective SPAN or mirror functions).
  • Packet broker 106 can perform various packet processing functions on the replicated traffic, such as removing protocol headers, filtering/classifying packets based on user-defined filters/rules, and so on.
  • Packet broker 106 can then forward the processed traffic to one or more analytic probes/tools 108, which can carry out various calculations and analyses on the traffic in accordance with the business goals/purposes of visibility network 100.
  • analytic probes/tools 108 can carry out various calculations and analyses on the traffic in accordance with the business goals/purposes of visibility network 100.
  • existing packet brokers can accept and apply user- defined filters that are based on parameters explicitly present in the traffic replicated from a core network (referred to herein as "first-order" parameters). For example, assume that core network 104 of FIG. 1 is a mobile network and that the traffic replicated from core network 104 is GTP-C/GTP-U traffic.
  • packet broker 106 can accept/apply user-defined filters based on first-order parameters that explicitly appear in GTP traffic such as IMS I, ⁇ , APN, QCI, RAT, ULI, etc.
  • first-order parameters such as IMS I, ⁇ , APN, QCI, RAT, ULI, etc.
  • second-order parameters that may be associated with, but are not explicitly present in, the traffic replicated from the core network
  • packet broker 106 cannot accept/apply user-defined filters based on second-order parameters that do not appear in GTP traffic such as, e.g., characteristics of the end-user device connected to a particular GTP session (CPU type, RAM amount, screen size, device type, etc.), geographic location of the end-user device, and others.
  • an operator of a visibility network wishes to analyze replicated traffic based on second-order parameters, it is possible to work around this limitation by configuring the network's packet broker to forward all replicated traffic to the analytic probes/tools.
  • the analytic probes/tools can then store the traffic and perform a post-hoc analysis of the stored data to identify the packets of interest.
  • this approach will generally require a significant amount of compute and storage resources on the analytic probes/tools in order to store and analyze all of the replicated traffic, which undesirably increases the cost and complexity of the visibility network.
  • the smart filter generator can maintain at least one mapping between (1) a first-order parameter found in network traffic replicated from a core network monitored by the visibility network, and (2) a second-order parameter related to the first-order parameter, where the second-order parameter is not found in the network traffic replicated from the core network.
  • the smart filter generator can further receive, from a user, a user-defined packet filter definition comprising a filtering criterion that makes use of the second-order parameter.
  • the smart filter generator can then translate, based on the at least one mapping, the filtering criterion into a version that makes use of the first-order parameter, and can generate a new packet filter comprising the translated version of the filtering criterion.
  • FIG. 1 depicts an example visibility network.
  • FIG. 2 depicts a visibility network comprising a smart filter generator according to an embodiment.
  • FIG. 3 depicts a workflow for that can be executed by the smart filter generator of FIG. 2 according to an embodiment.
  • FIG. 4 depicts an example architecture for the smart filter generator of FIG. 2 according to an embodiment.
  • FIG. 5 depicts an example network switch/router according to an embodiment.
  • FIG. 6 depicts an example computer system according to an embodiment.
  • Embodiments of the present disclosure describe a smart filter generator that can communicate with, or be integrated within, a packet broker of a visibility network to facilitate the filtering of traffic replicated from a core network based on second-order parameters (i.e., parameters that are not explicitly present in the replicated traffic).
  • the smart filter generator can maintain a knowledge base comprising one or more sets of mappings between (1) second-order parameters that a user may be interested in using as a basis for filtering traffic from the core network, and (2) first-order parameters associated with the second-order parameters.
  • the knowledge base may comprise a first set of mappings between various user equipment (UE) device characteristics (second-order parameters) and IMEI TAC (first-order parameter); a second set of mappings between various geographic identifiers or classifiers (second-order parameters) and EnodeB ID/IP address (first-order parameters); a third set of mappings between various UE software/browser/OS identifiers (second-order parameters) and a user agent string (first-order parameter); and so on.
  • UE user equipment
  • second-order parameters user equipment
  • IMEI TAC first-order parameter
  • second-order parameters second set of mappings between various geographic identifiers or classifiers
  • EnodeB ID/IP address first-order parameters
  • third set of mappings between various UE software/browser/OS identifiers second-order parameters
  • user agent string first-order parameter
  • the smart filter generator can further receive, from a user, a packet filter definition that includes a filtering criterion comprising one or more of the second-order parameters included in the knowledge base and one or more corresponding values.
  • a packet filter definition that includes a filtering criterion comprising one or more of the second-order parameters included in the knowledge base and one or more corresponding values.
  • the smart filter generator can consult the knowledge base and translate, based on the mappings in the knowledge base, the second-order parameters and values included in the filtering criterion into corresponding first-order parameters and values. For example, returning to the example above, the smart filter generator can access the device database of the knowledge base and retrieve a list of all IMEI TACs mapped to the device type "iPhone.” [0019] The smart filter generator can then generate a new packet filter definition that includes, as its filtering criterion, the one or more first-order parameters and values determined via the translation.
  • this newly generated packet filter definition can be communicated to the packet broker, which can apply the packet filter (in the form of, e.g., an access control list, or ACL) to traffic that is replicated/received from the core network.
  • the packet filter in the form of, e.g., an access control list, or ACL
  • the smart filter generator can enable the packet broker to effectively accept and apply user-defined packet filters that are based on second-order parameters not typically found in that traffic. This allows the visibility network to identify/analyze traffic based on such parameters, without needing to perform resource- intensive post-hoc analysis or querying on the analytic probes/tools. As a result, the complexity and cost of the visibility network (in particular with respect to the
  • FIG. 2 depicts a visibility network 200 in accordance with an embodiment of the present disclosure.
  • visibility network 200 includes a number of taps 202 that are deployed in a core network 204 and are configured to replicate traffic exchanged in network 204 to a packet broker 206.
  • core network 204 is a mobile LTE network that comprises network elements specific to this type of network, such as an eNodeB 210, a mobility management entity (MME) 212, a serving gateway (SGW) 214, and a packet data network gateway (PGW) 216 which connects to an external packet data network such as the Internet.
  • taps 202 are configured to replicate and forward GTP-C and GTP-U traffic that is exchanged on certain interfaces of core network 204.
  • core network 204 can be any other type of computer network known in the art, such as a mobile 3G network, a landline local area network (LAN) or wide area network (WAN), etc.
  • LAN local area network
  • WAN wide area network
  • packet broker 206 can perform various types of packet processing functions on the traffic (e.g., filtering, classifying, correlating, etc.) as configured by a user/administrator and can forward the processed traffic to one or more analytic probes/tools 208 for analysis.
  • packet broker 206 can be implemented solely in hardware, such as in the form of a network switch or router that relies on ASIC or FPGA-based packet processors to execute its assigned packet processing functions based on rules that are programmed into hardware memory tables (e.g., CAM tables) resident on the packet processors and/or line cards of the device.
  • hardware memory tables e.g., CAM tables
  • packet broker 206 can be implemented solely in software that runs on, e.g., one or more general purpose physical or virtual computer systems.
  • packet broker 206 can be implemented using a combination of hardware and software, such as a combination of a hardware -based basic packet broker and a software-based "session director" cluster as described in co-owned U.S. Patent Application No. 15/205,889, entitled “Software-based Packet Broker,” the entire contents of which are incorporated herein by reference in its entirety for all purposes.
  • existing packet brokers can accept and apply user-defined packet filters that filter replicated traffic based on first-order parameters (i.e., parameters that are present in the replicated traffic)
  • existing packet brokers generally cannot filter replicated traffic based on second-order parameters (i.e., parameters which do not appear in the replicated traffic). It is possible to identify traffic that matches one or more second-order parameters by querying the analytic probes/tools of the visibility network or implementing additional/special probes in the core network to select the traffic of interest; however, these solutions generally increase the cost and complexity of the visibility network.
  • visibility network 200 of FIG. 2 is enhanced to include a novel smart filter generator (SFG) 218.
  • SFG 218 can be implemented in software, hardware, or a combination thereof. Further, SFG 218 can be implemented as an entity that is separate from packet broker 206 (as shown in FIG. 2), or as an integral component of packet broker 206. As described in further detail below, SFG 218 can enable packet broker 206 to extend its traffic filtering capabilities to filter replicated traffic from core network 204 based on second-order parameters that are not readily available in the replicated traffic.
  • Examples of such second-order parameters in the context of mobile LTE network 204 include end-user equipment capabilities, client browser type, roaming subscriber info, and geographic attributes (e.g., ZIP code, postal address, GPS coordinates, etc.).
  • SFG 218 can provide more flexible and useful filtering functions to the user/operators of visibility network 200, without increasing the cost and/or complexity of the network.
  • FIG. 2 is illustrative and not intended to limit embodiments of the present disclosure.
  • the various entities shown in FIG. 2 may be arranged according to different configurations and/or include subcomponents or functions that are not specifically described.
  • One of ordinary skill in the art will recognize other variations, modifications, and alternatives. 3. High-Level SFG Workflow and Architecture
  • FIG. 3 depicts a high-level workflow 300 that can be executed by SFG 218 of FIG. 2 to facilitate the filtering of replicated traffic on packet broker 206 based on second-order parameters according to an embodiment.
  • SFG 218 can receive, via one or more data provisioning interfaces (e.g., CSV using SCP or FTP, CLI, REST API using ISON or XML, SNMP, etc.), mappings between (1) second-order parameters that a user/operator of packet broker 206 may wish to use as a basis for filtering traffic from core network 204, and (2) first-order parameters that explicitly appear in that traffic.
  • data provisioning interfaces e.g., CSV using SCP or FTP, CLI, REST API using ISON or XML, SNMP, etc.
  • the second-order parameters may include UE device capabilities, geographic location information, user agent information, etc.
  • the first-order parameters may include IMSI, IMEI, APN, QCI, RAT, ULI, MCC, MNC, etc.
  • the mappings may be entered manually by a user or in an automated manner via a provisioning application or script.
  • SFG 218 can store the received mappings in a local knowledge base.
  • this knowledge base can comprise a number of separate databases, where each database is configured to maintain mappings for a particular related set of second-order and first-order parameters (e.g., one database for device capability-related parameters, another database for location-related parameters, etc.).
  • SFG 218 can receive, via a user configuration interface (e.g., CLI, REST API, etc.), a definition of a packet filter from a user, where the user-defined packet filter definition includes a filtering criterion based on second-order parameter P2 (block 306).
  • a user configuration interface e.g., CLI, REST API, etc.
  • SFG 218 can parse the user-defined packet filter definition, identify the use of second-order parameter P2 in the filter's filtering criterion, and translate, based on the mappings in the knowledge base, the filtering criterion into a version that makes use of corresponding first-order parameter PI (rather than second-order parameter P2).
  • SFG 218 can generate a new packet filter definition that makes use of the translated criterion (block 314). Finally, at block 316, SFG 218 can communicate the newly generated packet filter definition to packet broker 206, which in turn can configure itself to apply the packet filter (in the form of, e.g., an ACL) and thereby use it to filter replicated traffic received from core network 204.
  • packet broker 206 which in turn can configure itself to apply the packet filter (in the form of, e.g., an ACL) and thereby use it to filter replicated traffic received from core network 204.
  • blocks 302-304 (which pertain to the receipt and storage of parameter mappings in the knowledge base) may overlap with blocks 306-316 (which pertain to packet filter generation). This may occur if, e.g., SFG 218 receives additional/updated mapping information from users or from an automated provisioning component (e.g., a central support portal) on a periodic basis.
  • SFG 218 receives additional/updated mapping information from users or from an automated provisioning component (e.g., a central support portal) on a periodic basis.
  • an automated provisioning component e.g., a central support portal
  • FIG. 4 is a block diagram of one possible architecture (400) for SFG 218 according to an embodiment.
  • architecture 400 includes a provisioning sub-system 402 that exposes various provisioning interfaces (e.g., CSV, CLI, REST API, and SNMP) usable for populating a knowledge base 404 with parameter mappings.
  • provisioning interfaces e.g., CSV, CLI, REST API, and SNMP
  • this provisioning can be carried out manually by a user or automatically via, e.g., a remote update agent/server that is configured to update the contents of knowledge base 404 on a periodic basis.
  • Knowledge base 404 comprises a number of databases 406, 408, 410, and 412 which are used to store the parameter mapping data provisioned via provisioning sub-system 402.
  • Each of these databases may store parameter mappings pertaining to a particular type of filter that a user may wish to define; for example, in FIG. 4, knowledge base 404 includes device, location, user agent, and home network databases.
  • knowledge base 404 includes device, location, user agent, and home network databases.
  • these are merely exemplary and other types of databases are also possible.
  • the interface between provisioning sub-system 402 and knowledge base 404 can be, e.g., an ODBC interface if a MySQL-like database system is used.
  • the interface between provisioning sub-system 402 and knowledge base 404 can make use of standard inter-process communication (IPC) if a memory-based data structure is used to host the databases of knowledge base 404.
  • IPC inter-process communication
  • SFG architecture 400 further includes a user interface sub-system 414 and a filter generation subsystem 416.
  • user interface sub-system 414 exposes a CLI and/or REST API interface which enables one or more users to provide/enter packet filter definitions.
  • user interface subsystem 414 can pass the definition to filter generation sub-system 416.
  • filter generation sub-system 416 can parse the user-defined packet filter definition, translate the second-order parameters/values included in the filtering criteria of the user-defined packet definition into corresponding first-order parameters/values based on the parameter mappings in knowledge base 404, and generate a new packet filter definition with the translated criteria.
  • filter generation sub-system 416 can communicate the newly generated packet filter definition to packet broker 206 via an appropriate interface.
  • SFG 218 can communicate the packet filter definition (i.e., program it on the packet broker) using a local CLI interface.
  • SFG 218 can communicate the packet filter definition to packet broker 206 via a remote CLI interface or a REST API interface.
  • SFG 218 can communicate the packet filter definition to packet broker 206 via a remote CLI interface or a REST API interface.
  • UE end user equipment
  • This type of filter can enable a user to drop/redirect/replicate/sample the traffic generated by roaming subscribers.
  • the listing below shows an example set of CLI commands that may be entered by the user for providing a definition of this type of filter to SFG 218.
  • SFG 218 can use the "SEF" type field to query the home network database.
  • the result of this query is the network identifier (MNC and MCC) of the network on which the packet broker is deployed. This could be one pair of MCC-MNC or a list.
  • SFG 218 can then generate a new filter using wild cards, as IMSI has MCC and MNC as constituent fields.
  • this particular type of filter can be enhanced to filter based on name of the country of origin of subscribers. For example, subscribers roaming from Japan or USA can be filtered. This can be achieved by modifying the query to filter the given country name.
  • This type of filter can also be further enhanced to filter by the specific operator and/or country of origin of subscribers (e.g., Vodafone subscribers from the UK).
  • This type of filter can enable a user to drop/redirect/replicate/sample the traffic generated by subscribers who are tethering from their mobile devices.
  • the listing below shows an example set of CLI commands that may be entered by the user for providing a definition of this type of filter to SFG 218.
  • SFG 218 can use the "SEF" type field to query the device database.
  • Two values can be retrieved from the device database in response to this query: (1) an IMEI TAC code belonging to the device in input, and (2) Operating System.
  • the user agent database can be queried to extract the possible user agents the operating system may support. From these two lists, two packet filters can be generated and applied in succession (i.e., chained) on packet broker 206.
  • This type of filter can enable a user to drop/redirect/replicate the traffic generated by subscribers present in a particular location.
  • the listing below shows an example set of CLI commands that may be entered by the user for providing a definition of this type of filter to SFG 218.
  • SFG 218 can use the "SEF" type field to query the location database. The result of this query is a list of EnodeB IDs. SFG 218 can then generate a packet filter based on eNodeB ID and communicate the filter to packet broker 206.
  • this filter can be enhanced to filter based on postal address/ZIP code and/or the name of a particular city or region such as "South San Francisco
  • This type of filter can enable a user to drop/redirect/replicate the traffic generated from end user equipment with specific capabilities.
  • the listing below shows an example set of CLI commands that may be entered by the user for providing a definition of this type of filter to SFG 218.
  • SFG 218 Upon receiving this filter definition, SFG 218 can use the "SEF" type field to query the device database. The result of this query is a list of IMEI TAC codes. SFG 218 can then generate a packet filter based on the retrieved list of IMEI TACs and can communicate this filter to packet broker 206.
  • This type of filter enables a user to drop/redirect/replicate the traffic generated from a specific browser.
  • the listing below shows an example set of CLI commands that may be entered by the user for providing a definition of this type of filter to SFG 218.
  • SFG 218 can use the "SEF" type field to query the user agent database.
  • the result of this query is a list of user agents in regex format.
  • SFG 218 can then generate a packet filter based on the retrieved list and can communicate the filter to packet broker 206.
  • this filter action (which enables a user to generate S-Flow records for the traffic generated from a filter) can be added any of the filters described above.
  • the listing below shows an example set of CLI commands that may be entered by the user for enabling an S-Flow filter action with respect to a device-type filter.
  • SFG 218 can enable S-Flow records at the corresponding port of packet broker 206. Hence, S-Flow records belonging to the match in any filter can be generated. 5.
  • FIG. 5 depicts an example network device (e.g., switch/router) 500 according to an embodiment.
  • Network switch/router 500 can be used to implement (either wholly in in part) packet broker 206 described throughout this disclosure.
  • network switch/router 500 includes a management module 502, a switch fabric module 504, and a number of line cards 506(1 )-506(N).
  • Management module 502 includes one or more management CPUs 508 for managing/controlling the operation of the device.
  • Each management CPU 508 can be a general purpose processor, such as a PowerPC, Intel, AMD, or ARM-based processor, that operates under the control of software stored in an associated memory (not shown).
  • Switch fabric module 504 and line cards 506(1)-506(N) collectively represent the data, or forwarding, plane of network switch/router 500.
  • Switch fabric module 504 is configured to interconnect the various other modules of network switch/router 500.
  • Each line card 506(1)-506(N) can include one or more ingress/egress ports 510(1)-510(N) that are used by network switch/router 500 to send and receive packets.
  • Each line card 506(1)-506(N) can also include a packet processor 512(1)-512(N).
  • Packet processor 512(1)-512(N) is a hardware processing component (e.g., an FPGA or ASIC) that can make wire speed decisions on how to handle incoming or outgoing traffic.
  • network switch/router 500 is illustrative and not intended to limit embodiments of the present disclosure. Many other configurations having more or fewer components than switch/router 500 are possible. 6. Example Computer System
  • FIG. 6 depicts an example computer system 600 according to an embodiment.
  • Computer system 600 can be used to implement (either wholly or in part) packet broker 206 described throughout this disclosure.
  • computer system 600 can include one or more general purpose processors (e.g., CPUs) 602 that communicate with a number of peripheral devices via a bus subsystem 604.
  • peripheral devices can include a storage subsystem 606 (comprising a memory subsystem 608 and a file storage subsystem 610), user interface input devices 612, user interface output devices 614, and a network interface subsystem 616.
  • Bus subsystem 604 can provide a mechanism for letting the various components and subsystems of computer system 600 communicate with each other as intended. Although bus subsystem 604 is shown schematically as a single bus, alternative embodiments of the bus subsystem can utilize multiple buses.
  • Network interface subsystem 616 can serve as an interface for communicating data between computer system 600 and other computing devices or networks.
  • Embodiments of network interface subsystem 616 can include wired (e.g., coaxial, twisted pair, or fiber optic Ethernet) and/or wireless (e.g., Wi-Fi, cellular, Bluetooth, etc.) interfaces.
  • User interface input devices 612 can include a keyboard, pointing devices (e.g., mouse, trackball, touchpad, etc.), a scanner, a barcode scanner, a touch-screen incorporated into a display, audio input devices (e.g., voice recognition systems, microphones, etc.), and other types of input devices.
  • use of the term "input device” is intended to include all possible types of devices and mechanisms for inputting information into computer system 600.
  • User interface output devices 614 can include a display subsystem, a printer, a fax machine, or non-visual displays such as audio output devices, etc.
  • the display subsystem can be a cathode ray tube (CRT), a flat-panel device such as a liquid crystal display (LCD), or a projection device.
  • CTR cathode ray tube
  • LCD liquid crystal display
  • output device is intended to include all possible types of devices and mechanisms for outputting information from computer system 600.
  • Storage subsystem 606 can include a memory subsystem 608 and a file/disk storage subsystem 610.
  • Subsystems 608 and 610 represent non-transitory computer-readable storage media that can store program code and/or data that provide the functionality of various embodiments described herein.
  • Memory subsystem 608 can include a number of memories including a main random access memory (RAM) 618 for storage of instructions and data during program execution and a read-only memory (ROM) 620 in which fixed instructions are stored.
  • File storage subsystem 610 can provide persistent (i.e., nonvolatile) storage for program and data files and can include a magnetic or solid-state hard disk drive, an optical drive along with associated removable media (e.g., CD-ROM, DVD, Blu-Ray, etc.), a removable flash memory-based drive or card, and/or other types of storage media known in the art.
  • computer system 600 is illustrative and not intended to limit embodiments of the present disclosure. Many other configurations having more or fewer components than computer system 600 are possible.

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Abstract

L'invention concerne des techniques de mise en œuvre d'un générateur de filtre intelligent dans un réseau à visibilité. Dans un ensemble de modes de réalisation, le générateur de filtre intelligent peut maintenir au moins un mappage entre (1) un paramètre du premier ordre qui figure dans un trafic de réseau reproduit à partir d'un réseau central surveillé par le réseau à visibilité, et (2) un paramètre du second ordre lié au paramètre du premier ordre, le paramètre du second ordre ne figurant pas dans le trafic de réseau reproduit à partir du réseau central. Le générateur de filtre intelligent peut en outre recevoir, de la part d'un utilisateur, une définition de filtre de paquets définie par l'utilisateur comportant un critère de filtrage qui fait usage du paramètre du second ordre. Le générateur de filtre intelligent peut alors traduire, d'après le ou les mappages, le critère de filtrage en une version qui fait usage du paramètre du premier ordre, et peut générer un nouveau filtre de paquets comportant la version traduite du critère de filtrage.
PCT/US2017/055191 2016-10-19 2017-10-04 Générateur de filtre intelligent WO2018075249A1 (fr)

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US20180109433A1 (en) 2018-04-19

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